Zhichao Peng

Enhancing Logical Expressiveness in Graph Neural Networks via Path-Neighbor Aggregation

Graph neural networks (GNNs) can effectively model structural information of graphs, making them widely used in knowledge graph (KG) reasoning. However, existing studies on the expressive power of GNNs mainly focuses on simple single-relation graphs, and there is still insufficient discussion on the